def test_op_name_duplicated_many(self):
@mb.program(input_specs=[mb.TensorSpec(shape=(10, 20))])
def prog(x):
x = mb.cast(x=x, dtype="fp16", name="castop")
x = mb.cast(x=x, dtype="fp16", name="castop")
x = mb.cast(x=x, dtype="int32", name="castop_2")
x = mb.cast(x=x, dtype="int64", name="castop")
x = mb.cast(x=x, dtype="fp32", name="castop_2")
x = mb.square(x=x, name="square")
return x
prev_prog, _, block = apply_pass_and_basic_check(
prog, "common::dedup_op_and_var_names")
self.assertEqual(get_op_types_in_program(prev_prog),
['cast', 'cast', 'cast', 'cast', 'cast', 'square'])
self.assertEqual(
get_op_names_in_program(prev_prog),
['castop', 'castop', 'castop_2', 'castop', 'castop_2', 'square'])
self.assertEqual(get_op_types_in_program(prog),
['cast', 'cast', 'cast', 'cast', 'cast', 'square'])
self.assertEqual(get_op_names_in_program(prog), [
'castop', 'castop_1', 'castop_2', 'castop_3', 'castop_2_1',
'square'
])
assert_model_is_valid(
prog,
{"x": (10, 20)},
expected_output_shapes={block.outputs[0].name: (10, 20)},
)
def test_input_name_shadow(self):
@mb.program(input_specs=[mb.TensorSpec(shape=(10, 20))])
def prog(x):
# op name "x" results in output var name "x", which shadows prog
# input var name "x"
x = mb.transpose(x=x, perm=[1, 0], name="x")
x = mb.relu(x=x, name="relu")
return x
prev_prog, _, block = apply_pass_and_basic_check(
prog, "common::dedup_op_and_var_names")
self.assertEqual(get_op_types_in_program(prev_prog),
['transpose', 'relu'])
self.assertEqual(get_op_names_in_program(prev_prog), ['x', 'relu'])
self.assertEqual(get_op_types_in_program(prog), ['transpose', 'relu'])
self.assertEqual(get_op_names_in_program(prog), ['x', 'relu'])
op = prog['main'].find_ops(op_type='transpose')[0]
self.assertEqual("x_1", op.outputs[0].name)
assert_model_is_valid(
prog,
{"x": (10, 20)},
expected_output_shapes={block.outputs[0].name: (20, 10)},
)
def test_unchanged(self):
@mb.program(input_specs=[mb.TensorSpec(shape=(2, 4))])
def prog(x):
x = mb.reshape(x=x, shape=(1, 8), name="reshape")
return x
prev_prog, _, block = apply_pass_and_basic_check(
prog, "common::dedup_op_and_var_names")
self.assertEqual(get_op_types_in_program(prev_prog), ['reshape'])
self.assertEqual(get_op_names_in_program(prev_prog), ['reshape'])
self.assertEqual(get_op_types_in_program(prog), ['reshape'])
self.assertEqual(get_op_names_in_program(prog), ['reshape'])
assert_model_is_valid(
prog,
{"x": (2, 4)},
expected_output_shapes={block.outputs[0].name: (1, 8)},
)